The use of MLLS fitting approach to resolve overlapping edges in the EELS spectrum at the atomic level
The multiple linear least squares (MLLS) fitting routine provides a very useful means for mapping difference spectra phases or features by reference to their spectral signature. Once the MLLS is complete the algorithm returns the fit coefficients corresponding to the optimal linear combination of the specified reference spectra to the input data. In other words, the routine will fit reference spectra to a dataset and tell exactly how much of each reference is present. When applied to spectrum imaging, this technique becomes even more useful since not only how much of each reference is given but also its distribution. Hence if MLLS is correctly applied to a spectrum imaging (SI) dataset, it provides the ability to map the spatial distribution of the input reference spectra.